Minor updates to tests

src/rawDeepLearningClassifier/defaultModels/MultiSpeciesGoogle.java

@@ -71,7 +71,8 @@ public class MultiSpeciesGoogle implements DLModel {
 		//create the transforms. 
 		ArrayList<DLTransfromParams> dlTransformParamsArr = new ArrayList<DLTransfromParams>();
 
-		dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.DECIMATE_SCIPY, sr)); 
+		//Performed long series of test son which decimator is best for upsampling and it is, by far, the DECIMATE transform. 
+		dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.DECIMATE, sr)); 
 
 		genericModelParams.dlTransfromParams = dlTransformParamsArr;
 

src/test/export/ExportTest.java

@@ -3,6 +3,7 @@ package test.export;
 import test.helper.PamControllerTestHelper;
 import clickDetector.ClickControl;
 import clickDetector.ClickDetector;
+
 import org.junit.jupiter.api.Test;
 
 import clickDetector.ClickDetection;
@@ -21,7 +22,7 @@ public class ExportTest {
 	public void matFileTest() throws Exception {
 		PamControllerTestHelper.InitializePamControllerForTesting();
 
-		System.out.println("Matched template classifier test: match corr");
+		System.out.println("Export MATLAB TEST");
 
 		//create a list of click detections.
 		ClickControl control = new ClickControl("name");

src/test/noiseOneBand/OneBandControlTest.java

@@ -12,6 +12,7 @@ import static org.junit.jupiter.api.Assertions.assertEquals;
 import static org.junit.jupiter.api.Assertions.assertThrows;
 
 public class OneBandControlTest {
+	
     @BeforeAll
     public static void setUpBeforeClass() throws Exception {
         PamControllerTestHelper.InitializePamControllerForTesting();

src/test/rawDeepLearningClassifier/KooguDLClassifierTest.java

@@ -92,7 +92,7 @@ public class KooguDLClassifierTest {
 
 				GroupedRawData groupedRawData = new GroupedRawData(0, 1, 0, duration, (int) duration);
 
-				//koogu predictions are in sam,ples
+				//koogu predictions are in samples
 				int startChunk =(int) (kooguPredicitions[i][0]*soundData.sampleRate/250); ///the start chunk is in decimated samples - uuurgh
 				
 
@@ -101,7 +101,6 @@ public class KooguDLClassifierTest {
 				ArrayList<GroupedRawData> groupedData = new ArrayList<GroupedRawData>();
 				groupedData.add(groupedRawData);
 
-				
 				ArrayList<StandardPrediction> genericPrediciton = kooguWorker.runModel(groupedData, soundData.sampleRate, 0);		
 				float[] output =  genericPrediciton.get(0).getPrediction();
 
@@ -113,12 +112,14 @@ public class KooguDLClassifierTest {
 				if (testPassed) {
 					truecount++;
 				}
+				
+				
 			}
 			
 			//there are occasionaly slight differences between PMAGuard and Python so just make sure most data points are the same. 
 			double percTrue = 100*((double) truecount)/kooguPredicitions.length; 
 
-			System.out.println(String.format("Perecentage results true: %.2f  count %d", percTrue, truecount));
+			System.out.println(String.format("Percentage results true: %.2f  count %d", percTrue, truecount));
 			
 		    //at least 90% of results must match for the dataset
 			assertTrue(percTrue>0.9);

src/test/rawDeepLearningClassifier/PamZipDLClassifierTest.java

@@ -8,8 +8,6 @@ import java.nio.file.Path;
 import java.nio.file.Paths;
 import java.util.ArrayList;
 
-import org.jamdev.jdl4pam.transforms.DLTransform.DLTransformType;
-import org.jamdev.jdl4pam.transforms.SimpleTransformParams;
 import org.jamdev.jdl4pam.utils.DLMatFile;
 import org.jamdev.jdl4pam.utils.DLUtils;
 import org.jamdev.jpamutils.wavFiles.AudioData;
@@ -182,7 +180,11 @@ public class PamZipDLClassifierTest {
 
 		//path to the same file at different sample rates
 		String relWavPath  =	"./src/test/resources/rawDeepLearningClassifier/Generic/multi-species-Google/NOPP6_EST_20090329_121500.wav";
-		String relWavPath2  =	"./src/test/resources/rawDeepLearningClassifier/Generic/multi-species-Google/NOPP6_EST_20090329_121500_upsample.wav";
+		String relWavPath2  =	"./src/test/resources/rawDeepLearningClassifier/Generic/multi-species-Google/NOPP6_EST_20090329_121500_upsample_pg.wav";
+		
+		/**
+		 * Test up-sampling using audio then downsampling agian
+		 */
 //		String relWavPath2  =	"./src/test/resources/rawDeepLearningClassifier/Generic/multi-species-Google/NOPP6_EST_20090329_121500.wav";
 
 		String matFileOut = "/Users/jdjm/MATLAB-Drive/MATLAB/PAMGUARD/deep_learning/google_multi_species/google_multi_species.mat"; 
@@ -202,13 +204,13 @@ public class PamZipDLClassifierTest {
 
 		MultiSpeciesGoogle multiSpeciesGoogle = new MultiSpeciesGoogle();
 		multiSpeciesGoogle.setParams(genericModelParams);
-		genericModelParams.dlTransfromParams.set(0, new SimpleTransformParams(DLTransformType.DECIMATE, 24000.)); 
+		//genericModelParams.dlTransfromParams.set(0, new SimpleTransformParams(DLTransformType.DECIMATE, 24000.)); 
 
 		System.out.println(genericModelParams);
 
 		double segSize = 5.; //one second hop size.
 		double segHop = 5.; //one second hop size.
-		int classIndex = 5; //Right whale atlantic - jus for output
+		int classIndex = 5; //Right whale atlantic - just for output
 		
 		//create MatFile for saving the image data to. 
 		MatFile matFile = Mat5.newMatFile();
@@ -227,9 +229,12 @@ public class PamZipDLClassifierTest {
 
 				//load audio
 				AudioData soundData = DLUtils.loadWavFile(wavFilePath);
+				
+				//TEMP
 //				if (i==1) {
 //					soundData=soundData.interpolate(24000);
 //				}
+				//////
 
 				int nseg =  (int) (soundData.samples.length/(segHop*soundData.sampleRate)); 
 				float[][] outputs = new float[nseg][];